Overview

Dataset statistics

Number of variables27
Number of observations418
Missing cells1298
Missing cells (%)11.5%
Duplicate rows19
Duplicate rows (%)4.5%
Total size in memory763.2 KiB
Average record size in memory1.8 KiB

Variable types

Numeric7
Categorical18
Unsupported2

Alerts

user_id has constant value ""Constant
type has constant value ""Constant
has_glang_contrib has constant value ""Constant
Dataset has 19 (4.5%) duplicate rowsDuplicates
cefr_rate is highly overall correlated with completed_at and 11 other fieldsHigh correlation
completed_at is highly overall correlated with cefr_rate and 17 other fieldsHigh correlation
created_at is highly overall correlated with cefr_rate and 17 other fieldsHigh correlation
engine is highly overall correlated with cefr_rate and 13 other fieldsHigh correlation
event_id is highly overall correlated with completed_at and 11 other fieldsHigh correlation
fail is highly overall correlated with cefr_rate and 17 other fieldsHigh correlation
group_id is highly overall correlated with completed_at and 12 other fieldsHigh correlation
history is highly overall correlated with cefr_rate and 17 other fieldsHigh correlation
id is highly overall correlated with completed_at and 11 other fieldsHigh correlation
items is highly overall correlated with cefr_rate and 17 other fieldsHigh correlation
lesson_id is highly overall correlated with completed_at and 11 other fieldsHigh correlation
load is highly overall correlated with cefr_rate and 8 other fieldsHigh correlation
pass is highly overall correlated with cefr_rate and 18 other fieldsHigh correlation
points is highly overall correlated with history and 8 other fieldsHigh correlation
queues is highly overall correlated with cefr_rate and 19 other fieldsHigh correlation
round is highly overall correlated with completed_at and 13 other fieldsHigh correlation
rule is highly overall correlated with completed_at and 11 other fieldsHigh correlation
score is highly overall correlated with completed_at and 10 other fieldsHigh correlation
status is highly overall correlated with cefr_rate and 13 other fieldsHigh correlation
time_spent is highly overall correlated with history and 4 other fieldsHigh correlation
total_time is highly overall correlated with cefr_rate and 20 other fieldsHigh correlation
updated_at is highly overall correlated with cefr_rate and 20 other fieldsHigh correlation
score is highly imbalanced (62.7%)Imbalance
pass has 66 (15.8%) missing valuesMissing
fail has 132 (31.6%) missing valuesMissing
completed_at has 242 (57.9%) missing valuesMissing
total_time has 22 (5.3%) missing valuesMissing
class_test_id has 418 (100.0%) missing valuesMissing
attempted_sets has 418 (100.0%) missing valuesMissing
items is uniformly distributedUniform
pass is uniformly distributedUniform
fail is uniformly distributedUniform
created_at is uniformly distributedUniform
updated_at is uniformly distributedUniform
completed_at is uniformly distributedUniform
total_time is uniformly distributedUniform
queues is uniformly distributedUniform
class_test_id is an unsupported type, check if it needs cleaning or further analysisUnsupported
attempted_sets is an unsupported type, check if it needs cleaning or further analysisUnsupported
load has 22 (5.3%) zerosZeros
cefr_rate has 66 (15.8%) zerosZeros
points has 44 (10.5%) zerosZeros
time_spent has 22 (5.3%) zerosZeros

Reproduction

Analysis started2024-04-19 01:05:45.198989
Analysis finished2024-04-19 01:05:48.539420
Duration3.34 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24319.263
Minimum23692
Maximum25073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:48.574458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23692
5-th percentile23692
Q123754
median24084
Q325044
95-th percentile25073
Maximum25073
Range1381
Interquartile range (IQR)1290

Descriptive statistics

Standard deviation602.42483
Coefficient of variation (CV)0.024771508
Kurtosis-1.8308687
Mean24319.263
Median Absolute Deviation (MAD)357
Skewness0.26300496
Sum10165452
Variance362915.68
MonotonicityIncreasing
2024-04-19T06:50:48.628360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
23692 22
 
5.3%
24085 22
 
5.3%
25071 22
 
5.3%
25068 22
 
5.3%
25051 22
 
5.3%
25044 22
 
5.3%
25037 22
 
5.3%
24889 22
 
5.3%
24861 22
 
5.3%
24084 22
 
5.3%
Other values (9) 198
47.4%
ValueCountFrequency (%)
23692 22
5.3%
23727 22
5.3%
23733 22
5.3%
23735 22
5.3%
23754 22
5.3%
23755 22
5.3%
23756 22
5.3%
23759 22
5.3%
23892 22
5.3%
24084 22
5.3%
ValueCountFrequency (%)
25073 22
5.3%
25071 22
5.3%
25068 22
5.3%
25051 22
5.3%
25044 22
5.3%
25037 22
5.3%
24889 22
5.3%
24861 22
5.3%
24085 22
5.3%
24084 22
5.3%

user_id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.0 KiB
2534
418 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1672
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2534
2nd row2534
3rd row2534
4th row2534
5th row2534

Common Values

ValueCountFrequency (%)
2534 418
100.0%

Length

2024-04-19T06:50:48.684055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:48.730252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2534 418
100.0%

Most occurring characters

ValueCountFrequency (%)
2 418
25.0%
5 418
25.0%
3 418
25.0%
4 418
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 418
25.0%
5 418
25.0%
3 418
25.0%
4 418
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 418
25.0%
5 418
25.0%
3 418
25.0%
4 418
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 418
25.0%
5 418
25.0%
3 418
25.0%
4 418
25.0%

lesson_id
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1771.9474
Minimum921
Maximum2122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:48.775370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum921
5-th percentile921
Q11556
median2112
Q32118
95-th percentile2122
Maximum2122
Range1201
Interquartile range (IQR)562

Descriptive statistics

Standard deviation444.31582
Coefficient of variation (CV)0.25075001
Kurtosis-0.64663386
Mean1771.9474
Median Absolute Deviation (MAD)10
Skewness-0.94141431
Sum740674
Variance197416.55
MonotonicityNot monotonic
2024-04-19T06:50:48.828040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1855 22
 
5.3%
2114 22
 
5.3%
2121 22
 
5.3%
2122 22
 
5.3%
2118 22
 
5.3%
2120 22
 
5.3%
2117 22
 
5.3%
2116 22
 
5.3%
2115 22
 
5.3%
2112 22
 
5.3%
Other values (9) 198
47.4%
ValueCountFrequency (%)
921 22
5.3%
943 22
5.3%
944 22
5.3%
1187 22
5.3%
1556 22
5.3%
1615 22
5.3%
1616 22
5.3%
1855 22
5.3%
1856 22
5.3%
2112 22
5.3%
ValueCountFrequency (%)
2122 22
5.3%
2121 22
5.3%
2120 22
5.3%
2119 22
5.3%
2118 22
5.3%
2117 22
5.3%
2116 22
5.3%
2115 22
5.3%
2114 22
5.3%
2112 22
5.3%

group_id
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size25.0 KiB
1760
220 
1717
132 
1700
66 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1672
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1717
2nd row1717
3rd row1717
4th row1717
5th row1717

Common Values

ValueCountFrequency (%)
1760 220
52.6%
1717 132
31.6%
1700 66
 
15.8%

Length

2024-04-19T06:50:48.882965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:48.931734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1760 220
52.6%
1717 132
31.6%
1700 66
 
15.8%

Most occurring characters

ValueCountFrequency (%)
1 550
32.9%
7 550
32.9%
0 352
21.1%
6 220
 
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 550
32.9%
7 550
32.9%
0 352
21.1%
6 220
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 550
32.9%
7 550
32.9%
0 352
21.1%
6 220
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1672
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 550
32.9%
7 550
32.9%
0 352
21.1%
6 220
 
13.2%

event_id
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157001.58
Minimum19951
Maximum279721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:48.983870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19951
5-th percentile19951
Q120788
median279712
Q3279717
95-th percentile279721
Maximum279721
Range259770
Interquartile range (IQR)258929

Descriptive statistics

Standard deviation129508.45
Coefficient of variation (CV)0.82488629
Kurtosis-1.9983528
Mean157001.58
Median Absolute Deviation (MAD)9
Skewness-0.10581532
Sum65626660
Variance1.6772439 × 1010
MonotonicityNot monotonic
2024-04-19T06:50:49.040691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20789 22
 
5.3%
279713 22
 
5.3%
279720 22
 
5.3%
279721 22
 
5.3%
279717 22
 
5.3%
279719 22
 
5.3%
279716 22
 
5.3%
279715 22
 
5.3%
279714 22
 
5.3%
279712 22
 
5.3%
Other values (9) 198
47.4%
ValueCountFrequency (%)
19951 22
5.3%
19952 22
5.3%
19953 22
5.3%
20787 22
5.3%
20788 22
5.3%
20789 22
5.3%
20790 22
5.3%
21427 22
5.3%
21428 22
5.3%
279712 22
5.3%
ValueCountFrequency (%)
279721 22
5.3%
279720 22
5.3%
279719 22
5.3%
279718 22
5.3%
279717 22
5.3%
279716 22
5.3%
279715 22
5.3%
279714 22
5.3%
279713 22
5.3%
279712 22
5.3%

engine
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size31.7 KiB
linearStandAloneEngine
242 
carryForwardEngine
176 

Length

Max length22
Median length22
Mean length20.315789
Min length18

Characters and Unicode

Total characters8492
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlinearStandAloneEngine
2nd rowlinearStandAloneEngine
3rd rowlinearStandAloneEngine
4th rowlinearStandAloneEngine
5th rowlinearStandAloneEngine

Common Values

ValueCountFrequency (%)
linearStandAloneEngine 242
57.9%
carryForwardEngine 176
42.1%

Length

2024-04-19T06:50:49.107823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:49.163278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
linearstandaloneengine 242
57.9%
carryforwardengine 176
42.1%

Most occurring characters

ValueCountFrequency (%)
n 1562
18.4%
r 946
11.1%
e 902
10.6%
a 836
9.8%
i 660
7.8%
l 484
 
5.7%
o 418
 
4.9%
g 418
 
4.9%
E 418
 
4.9%
d 418
 
4.9%
Other values (7) 1430
16.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8492
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1562
18.4%
r 946
11.1%
e 902
10.6%
a 836
9.8%
i 660
7.8%
l 484
 
5.7%
o 418
 
4.9%
g 418
 
4.9%
E 418
 
4.9%
d 418
 
4.9%
Other values (7) 1430
16.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8492
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1562
18.4%
r 946
11.1%
e 902
10.6%
a 836
9.8%
i 660
7.8%
l 484
 
5.7%
o 418
 
4.9%
g 418
 
4.9%
E 418
 
4.9%
d 418
 
4.9%
Other values (7) 1430
16.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8492
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1562
18.4%
r 946
11.1%
e 902
10.6%
a 836
9.8%
i 660
7.8%
l 484
 
5.7%
o 418
 
4.9%
g 418
 
4.9%
E 418
 
4.9%
d 418
 
4.9%
Other values (7) 1430
16.8%

items
Categorical

HIGH CORRELATION  UNIFORM 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size47.8 KiB
[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
 
22
[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685]
 
22
[45704, 45705, 45706, 45707]
 
22
[47871, 47877, 47880]
 
22
[18243, 18237, 18240, 18241, 18244, 18245]
 
22
Other values (14)
308 

Length

Max length70
Median length70
Mean length59.684211
Min length21

Characters and Unicode

Total characters24948
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
2nd row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
3rd row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
4th row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
5th row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]

Common Values

ValueCountFrequency (%)
[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823] 22
 
5.3%
[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685] 22
 
5.3%
[45704, 45705, 45706, 45707] 22
 
5.3%
[47871, 47877, 47880] 22
 
5.3%
[18243, 18237, 18240, 18241, 18244, 18245] 22
 
5.3%
[18227, 18235, 18225] 22
 
5.3%
[18215, 18223, 18213, 18214, 18216, 18218, 18219, 18220] 22
 
5.3%
[46120, 46127, 46157, 46163, 46169, 46174, 46185, 46187, 46194, 46197] 22
 
5.3%
[46208, 46209, 46210, 46211, 46212, 46213, 46214, 46215, 46216, 46217] 22
 
5.3%
[54546, 54547, 54548, 54549, 54550, 54551, 54847, 54553, 54554, 54555] 22
 
5.3%
Other values (9) 198
47.4%

Length

2024-04-19T06:50:49.220115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
45764 22
 
0.6%
54800 22
 
0.6%
54593 22
 
0.6%
54596 22
 
0.6%
54598 22
 
0.6%
54602 22
 
0.6%
54604 22
 
0.6%
54606 22
 
0.6%
54607 22
 
0.6%
54608 22
 
0.6%
Other values (152) 3344
93.8%

Most occurring characters

ValueCountFrequency (%)
5 3718
14.9%
4 3586
14.4%
, 3146
12.6%
3146
12.6%
8 2090
8.4%
7 1760
7.1%
6 1716
6.9%
1 1672
6.7%
2 1342
 
5.4%
0 858
 
3.4%
Other values (4) 1914
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24948
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 3718
14.9%
4 3586
14.4%
, 3146
12.6%
3146
12.6%
8 2090
8.4%
7 1760
7.1%
6 1716
6.9%
1 1672
6.7%
2 1342
 
5.4%
0 858
 
3.4%
Other values (4) 1914
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24948
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 3718
14.9%
4 3586
14.4%
, 3146
12.6%
3146
12.6%
8 2090
8.4%
7 1760
7.1%
6 1716
6.9%
1 1672
6.7%
2 1342
 
5.4%
0 858
 
3.4%
Other values (4) 1914
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24948
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 3718
14.9%
4 3586
14.4%
, 3146
12.6%
3146
12.6%
8 2090
8.4%
7 1760
7.1%
6 1716
6.9%
1 1672
6.7%
2 1342
 
5.4%
0 858
 
3.4%
Other values (4) 1914
7.7%

load
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2105263
Minimum0
Maximum9
Zeros22
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:49.269267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q39
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1085377
Coefficient of variation (CV)0.50052725
Kurtosis-1.0492844
Mean6.2105263
Median Absolute Deviation (MAD)1
Skewness-0.71626396
Sum2596
Variance9.6630064
MonotonicityNot monotonic
2024-04-19T06:50:49.316060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
9 154
36.8%
8 66
15.8%
2 44
 
10.5%
7 44
 
10.5%
3 22
 
5.3%
5 22
 
5.3%
1 22
 
5.3%
0 22
 
5.3%
4 22
 
5.3%
ValueCountFrequency (%)
0 22
 
5.3%
1 22
 
5.3%
2 44
 
10.5%
3 22
 
5.3%
4 22
 
5.3%
5 22
 
5.3%
7 44
 
10.5%
8 66
15.8%
9 154
36.8%
ValueCountFrequency (%)
9 154
36.8%
8 66
15.8%
7 44
 
10.5%
5 22
 
5.3%
4 22
 
5.3%
3 22
 
5.3%
2 44
 
10.5%
1 22
 
5.3%
0 22
 
5.3%

pass
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct16
Distinct (%)4.5%
Missing66
Missing (%)15.8%
Memory size35.8 KiB
[26680, 26681, 26686, 26683, 26684, 26685]
 
22
[45708, 45709, 45710, 45711, 45712, 45713, 45706, 45707]
 
22
[47692, 47857, 47860, 47863, 47866, 47883, 47874, 47871]
 
22
[18246, 18239, 18242, 18248, 18238, 18247, 18243, 18240]
 
22
[18230]
 
22
Other values (11)
242 

Length

Max length70
Median length63
Mean length40.6875
Min length7

Characters and Unicode

Total characters14322
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823]
2nd row[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823]
3rd row[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823]
4th row[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823]
5th row[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823]

Common Values

ValueCountFrequency (%)
[26680, 26681, 26686, 26683, 26684, 26685] 22
 
5.3%
[45708, 45709, 45710, 45711, 45712, 45713, 45706, 45707] 22
 
5.3%
[47692, 47857, 47860, 47863, 47866, 47883, 47874, 47871] 22
 
5.3%
[18246, 18239, 18242, 18248, 18238, 18247, 18243, 18240] 22
 
5.3%
[18230] 22
 
5.3%
[18217] 22
 
5.3%
[46157] 22
 
5.3%
[46208, 46209] 22
 
5.3%
[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823] 22
 
5.3%
[54780, 54777, 54778, 54779] 22
 
5.3%
Other values (6) 132
31.6%
(Missing) 66
15.8%

Length

2024-04-19T06:50:49.446847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
26680 22
 
1.1%
54606 22
 
1.1%
54794 22
 
1.1%
54793 22
 
1.1%
54792 22
 
1.1%
54791 22
 
1.1%
54608 22
 
1.1%
54598 22
 
1.1%
54596 22
 
1.1%
54609 22
 
1.1%
Other values (83) 1826
89.2%

Most occurring characters

ValueCountFrequency (%)
4 1980
13.8%
5 1892
13.2%
, 1694
11.8%
1694
11.8%
8 1650
11.5%
7 1122
7.8%
6 748
 
5.2%
1 748
 
5.2%
2 704
 
4.9%
0 638
 
4.5%
Other values (4) 1452
10.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14322
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 1980
13.8%
5 1892
13.2%
, 1694
11.8%
1694
11.8%
8 1650
11.5%
7 1122
7.8%
6 748
 
5.2%
1 748
 
5.2%
2 704
 
4.9%
0 638
 
4.5%
Other values (4) 1452
10.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14322
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 1980
13.8%
5 1892
13.2%
, 1694
11.8%
1694
11.8%
8 1650
11.5%
7 1122
7.8%
6 748
 
5.2%
1 748
 
5.2%
2 704
 
4.9%
0 638
 
4.5%
Other values (4) 1452
10.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14322
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 1980
13.8%
5 1892
13.2%
, 1694
11.8%
1694
11.8%
8 1650
11.5%
7 1122
7.8%
6 748
 
5.2%
1 748
 
5.2%
2 704
 
4.9%
0 638
 
4.5%
Other values (4) 1452
10.1%

fail
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct13
Distinct (%)4.5%
Missing132
Missing (%)31.6%
Memory size25.3 KiB
[45764, 45765]
22 
[26687, 26688, 26689, 26682]
22 
[45704, 45705]
22 
[47877, 47880]
22 
[18237, 18241, 18244]
22 
Other values (8)
176 

Length

Max length56
Median length35
Mean length18.307692
Min length7

Characters and Unicode

Total characters5236
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[45764, 45765]
2nd row[45764, 45765]
3rd row[45764, 45765]
4th row[45764, 45765]
5th row[45764, 45765]

Common Values

ValueCountFrequency (%)
[45764, 45765] 22
 
5.3%
[26687, 26688, 26689, 26682] 22
 
5.3%
[45704, 45705] 22
 
5.3%
[47877, 47880] 22
 
5.3%
[18237, 18241, 18244] 22
 
5.3%
[18227] 22
 
5.3%
[46120, 46127, 46163, 46169, 46174, 46185, 46187, 46194] 22
 
5.3%
[46210] 22
 
5.3%
[54546, 54550, 54551, 54847, 54553] 22
 
5.3%
[54602, 54604] 22
 
5.3%
Other values (3) 66
15.8%
(Missing) 132
31.6%

Length

2024-04-19T06:50:49.504372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
45764 22
 
2.9%
54551 22
 
2.9%
46185 22
 
2.9%
46187 22
 
2.9%
46194 22
 
2.9%
46210 22
 
2.9%
54546 22
 
2.9%
54550 22
 
2.9%
54847 22
 
2.9%
45765 22
 
2.9%
Other values (24) 528
70.6%

Most occurring characters

ValueCountFrequency (%)
4 792
15.1%
5 550
10.5%
6 550
10.5%
, 462
8.8%
462
8.8%
1 418
8.0%
8 396
7.6%
7 352
6.7%
2 308
 
5.9%
[ 286
 
5.5%
Other values (4) 660
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5236
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 792
15.1%
5 550
10.5%
6 550
10.5%
, 462
8.8%
462
8.8%
1 418
8.0%
8 396
7.6%
7 352
6.7%
2 308
 
5.9%
[ 286
 
5.5%
Other values (4) 660
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5236
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 792
15.1%
5 550
10.5%
6 550
10.5%
, 462
8.8%
462
8.8%
1 418
8.0%
8 396
7.6%
7 352
6.7%
2 308
 
5.9%
[ 286
 
5.5%
Other values (4) 660
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5236
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 792
15.1%
5 550
10.5%
6 550
10.5%
, 462
8.8%
462
8.8%
1 418
8.0%
8 396
7.6%
7 352
6.7%
2 308
 
5.9%
[ 286
 
5.5%
Other values (4) 660
12.6%

round
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
1
242 
2
88 
4
66 
3
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters418
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

Length

2024-04-19T06:50:49.556937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:49.606646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

Most occurring characters

ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 242
57.9%
2 88
 
21.1%
4 66
 
15.8%
3 22
 
5.3%

status
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size26.9 KiB
passed
176 
in_progress
154 
assessment
88 

Length

Max length11
Median length10
Mean length8.6842105
Min length6

Characters and Unicode

Total characters3630
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpassed
2nd rowpassed
3rd rowpassed
4th rowpassed
5th rowpassed

Common Values

ValueCountFrequency (%)
passed 176
42.1%
in_progress 154
36.8%
assessment 88
21.1%

Length

2024-04-19T06:50:49.663230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:49.713575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
passed 176
42.1%
in_progress 154
36.8%
assessment 88
21.1%

Most occurring characters

ValueCountFrequency (%)
s 1012
27.9%
e 506
13.9%
p 330
 
9.1%
r 308
 
8.5%
a 264
 
7.3%
n 242
 
6.7%
d 176
 
4.8%
i 154
 
4.2%
_ 154
 
4.2%
o 154
 
4.2%
Other values (3) 330
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3630
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1012
27.9%
e 506
13.9%
p 330
 
9.1%
r 308
 
8.5%
a 264
 
7.3%
n 242
 
6.7%
d 176
 
4.8%
i 154
 
4.2%
_ 154
 
4.2%
o 154
 
4.2%
Other values (3) 330
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3630
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1012
27.9%
e 506
13.9%
p 330
 
9.1%
r 308
 
8.5%
a 264
 
7.3%
n 242
 
6.7%
d 176
 
4.8%
i 154
 
4.2%
_ 154
 
4.2%
o 154
 
4.2%
Other values (3) 330
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3630
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1012
27.9%
e 506
13.9%
p 330
 
9.1%
r 308
 
8.5%
a 264
 
7.3%
n 242
 
6.7%
d 176
 
4.8%
i 154
 
4.2%
_ 154
 
4.2%
o 154
 
4.2%
Other values (3) 330
 
9.1%

history
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size326.5 KiB
{"skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}
44 
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}
 
22
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [45708, 45709, 45710, 45711, 45712, 45713], "points": 35, "attempted": [45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713], "cefr_rate": 18.75, "created_at": "2024-03-06T04:21:19.940552Z", "lang_level": 1, "time_spent": "250"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [], "points": 36, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 18.75, "created_at": "2024-03-06T04:24:16.034067Z", "lang_level": 1, "time_spent": "300"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705], "passed": [45706, 45707], "points": 58, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 25, "created_at": "2024-03-06T05:14:42.956894Z", "lang_level": 1, "time_spent": "328"}}, "cefr_rate": {"1709689884": 8.33333333, "1709689885": 12.5, "1709689886": 18.75, "1709689887": 18.75, "1709689888": 18.75, "1709689889": 18.75, "1709689890": 18.75, "1709689891": 18.75, "1709689892": 18.75, "1709689893": 18.75, "1709689894": 21.875}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:14:42.956942Z", "streak_badge_given_at_index": 8, "perseverance_badge_given_at_index": 3}
 
22
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [47692, 47857, 47860, 47863, 47866, 47883], "points": 33, "attempted": [47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:12:51.624980Z", "lang_level": 1, "time_spent": "379"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [], "points": 34, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:14:17.787087Z", "lang_level": 1, "time_spent": "386"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47877, 47880], "passed": [47874], "points": 40, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 14.880952385, "created_at": "2024-03-06T05:23:03.040310Z", "lang_level": 1, "time_spent": "453"}, "4": {"score": 0, "engine": "carryForwardEngine", "failed": [47877, 47880], "passed": [47871], "points": 55, "attempted": [47871, 47877, 47880], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:24:27.318589Z", "lang_level": 1, "time_spent": "456"}}, "cefr_rate": {"1709691177": 25, "1709691178": 25, "1709691179": 25, "1709691180": 25, "1709691181": 25, "1709691182": 20.83333333, "1709691183": 17.85714286, "1709691184": 17.85714286, "1709691185": 17.85714286, "1709691186": 13.095238095, "1709691187": 13.095238095, "1709691188": 13.095238095, "1709691189": 13.095238095, "1709691190": 14.880952385, "1709691191": 14.880952385, "1709691192": 16.666666665, "1709691193": 16.666666665}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1856, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:24:27.318622Z", "streak_badge_given_at_index": 4, "perseverance_badge_given_at_index": 3}
 
22
{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18246], "passed": [], "points": 0, "attempted": [18238, 18243, 18246], "cefr_rate": 0, "created_at": "2024-03-06T05:31:34.736440Z", "lang_level": 1, "time_spent": "244"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "passed": [18246, 18239, 18242, 18248], "points": 22, "attempted": [18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:37:32.250476Z", "lang_level": 1, "time_spent": "286"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [18243, 18237, 18240, 18241, 18244, 18245], "passed": [18238, 18247], "points": 35, "attempted": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "cefr_rate": 16.666666666666668, "created_at": "2024-03-06T13:01:24.927075Z", "lang_level": 1, "time_spent": "294"}}, "cefr_rate": {"1709703166": 25, "1709703167": 25, "1709703168": 25, "1709703169": 25, "1709703170": 25, "1709703171": 25, "1709703172": 25, "1709703173": 25, "1709703174": 25, "1709703175": 20.833333335, "1709703176": 20.833333335, "1709703177": 20.833333335, "1709703178": 20.833333335, "1709703179": 20.833333335, "1709703180": 20.833333335, "1709703181": 20.833333335, "1709703182": 19.444444446666665, "1709703183": 19.444444446666665, "1709703184": 22.222222223333333, "1709703185": 22.222222223333333, "1709703186": 22.222222223333333}, "skills_count": {"reading": 1, "writing": 1, "listening": 1}, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 4}
 
22
Other values (13)
286 

Length

Max length1883
Median length798
Mean length742.52632
Min length69

Characters and Unicode

Total characters310376
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}
2nd row{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}
3rd row{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}
4th row{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}
5th row{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}

Common Values

ValueCountFrequency (%)
{"skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true} 44
 
10.5%
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6} 22
 
5.3%
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [45708, 45709, 45710, 45711, 45712, 45713], "points": 35, "attempted": [45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713], "cefr_rate": 18.75, "created_at": "2024-03-06T04:21:19.940552Z", "lang_level": 1, "time_spent": "250"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [], "points": 36, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 18.75, "created_at": "2024-03-06T04:24:16.034067Z", "lang_level": 1, "time_spent": "300"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705], "passed": [45706, 45707], "points": 58, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 25, "created_at": "2024-03-06T05:14:42.956894Z", "lang_level": 1, "time_spent": "328"}}, "cefr_rate": {"1709689884": 8.33333333, "1709689885": 12.5, "1709689886": 18.75, "1709689887": 18.75, "1709689888": 18.75, "1709689889": 18.75, "1709689890": 18.75, "1709689891": 18.75, "1709689892": 18.75, "1709689893": 18.75, "1709689894": 21.875}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:14:42.956942Z", "streak_badge_given_at_index": 8, "perseverance_badge_given_at_index": 3} 22
 
5.3%
{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [47692, 47857, 47860, 47863, 47866, 47883], "points": 33, "attempted": [47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:12:51.624980Z", "lang_level": 1, "time_spent": "379"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [], "points": 34, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:14:17.787087Z", "lang_level": 1, "time_spent": "386"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47877, 47880], "passed": [47874], "points": 40, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 14.880952385, "created_at": "2024-03-06T05:23:03.040310Z", "lang_level": 1, "time_spent": "453"}, "4": {"score": 0, "engine": "carryForwardEngine", "failed": [47877, 47880], "passed": [47871], "points": 55, "attempted": [47871, 47877, 47880], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:24:27.318589Z", "lang_level": 1, "time_spent": "456"}}, "cefr_rate": {"1709691177": 25, "1709691178": 25, "1709691179": 25, "1709691180": 25, "1709691181": 25, "1709691182": 20.83333333, "1709691183": 17.85714286, "1709691184": 17.85714286, "1709691185": 17.85714286, "1709691186": 13.095238095, "1709691187": 13.095238095, "1709691188": 13.095238095, "1709691189": 13.095238095, "1709691190": 14.880952385, "1709691191": 14.880952385, "1709691192": 16.666666665, "1709691193": 16.666666665}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1856, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:24:27.318622Z", "streak_badge_given_at_index": 4, "perseverance_badge_given_at_index": 3} 22
 
5.3%
{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18246], "passed": [], "points": 0, "attempted": [18238, 18243, 18246], "cefr_rate": 0, "created_at": "2024-03-06T05:31:34.736440Z", "lang_level": 1, "time_spent": "244"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "passed": [18246, 18239, 18242, 18248], "points": 22, "attempted": [18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:37:32.250476Z", "lang_level": 1, "time_spent": "286"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [18243, 18237, 18240, 18241, 18244, 18245], "passed": [18238, 18247], "points": 35, "attempted": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "cefr_rate": 16.666666666666668, "created_at": "2024-03-06T13:01:24.927075Z", "lang_level": 1, "time_spent": "294"}}, "cefr_rate": {"1709703166": 25, "1709703167": 25, "1709703168": 25, "1709703169": 25, "1709703170": 25, "1709703171": 25, "1709703172": 25, "1709703173": 25, "1709703174": 25, "1709703175": 20.833333335, "1709703176": 20.833333335, "1709703177": 20.833333335, "1709703178": 20.833333335, "1709703179": 20.833333335, "1709703180": 20.833333335, "1709703181": 20.833333335, "1709703182": 19.444444446666665, "1709703183": 19.444444446666665, "1709703184": 22.222222223333333, "1709703185": 22.222222223333333, "1709703186": 22.222222223333333}, "skills_count": {"reading": 1, "writing": 1, "listening": 1}, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 4} 22
 
5.3%
{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18227, 18235], "passed": [18230], "points": 5, "attempted": [18227, 18230, 18235], "cefr_rate": 25, "created_at": "2024-03-06T05:43:24.441419Z", "lang_level": 1, "time_spent": "185"}}, "cefr_rate": {"1709703758": 25, "1709703759": 25}, "skills_count": {"reading": 1, "listening": 2}, "weakest_skill": "listening", "is_weakest_skill_on": true} 22
 
5.3%
{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18215, 18223], "passed": [18217], "points": 5, "attempted": [18215, 18217, 18223], "cefr_rate": 25, "created_at": "2024-03-06T05:54:55.204051Z", "lang_level": 1, "time_spent": "153"}}, "cefr_rate": {"1709704027": 25}, "skills_count": {"writing": 1, "listening": 2}, "weakest_skill": "listening", "is_weakest_skill_on": true} 22
 
5.3%
{"cefr_rate": {"1709725577": 50, "1709725578": 25, "1709725579": 16.66666667, "1709725580": 12.5, "1709725581": 12.5, "1709725582": 12.5, "1709725583": 12.5}, "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 6} 22
 
5.3%
{"cefr_rate": {"1710242548": 50, "1710242549": 50}, "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true} 22
 
5.3%
{"skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 6} 22
 
5.3%
Other values (8) 176
42.1%

Length

2024-04-19T06:50:49.776692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
25 1430
 
4.9%
1 902
 
3.1%
cefr_rate 858
 
3.0%
0 858
 
3.0%
638
 
2.2%
true 594
 
2.0%
score 506
 
1.7%
failed 506
 
1.7%
points 506
 
1.7%
attempted 506
 
1.7%
Other values (384) 21692
74.8%

Most occurring characters

ValueCountFrequency (%)
" 28600
 
9.2%
28578
 
9.2%
, 16456
 
5.3%
e 15202
 
4.9%
1 14652
 
4.7%
: 13486
 
4.3%
7 13156
 
4.2%
5 13156
 
4.2%
4 11946
 
3.8%
8 11946
 
3.8%
Other values (40) 143198
46.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 310376
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 28600
 
9.2%
28578
 
9.2%
, 16456
 
5.3%
e 15202
 
4.9%
1 14652
 
4.7%
: 13486
 
4.3%
7 13156
 
4.2%
5 13156
 
4.2%
4 11946
 
3.8%
8 11946
 
3.8%
Other values (40) 143198
46.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 310376
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 28600
 
9.2%
28578
 
9.2%
, 16456
 
5.3%
e 15202
 
4.9%
1 14652
 
4.7%
: 13486
 
4.3%
7 13156
 
4.2%
5 13156
 
4.2%
4 11946
 
3.8%
8 11946
 
3.8%
Other values (40) 143198
46.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 310376
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 28600
 
9.2%
28578
 
9.2%
, 16456
 
5.3%
e 15202
 
4.9%
1 14652
 
4.7%
: 13486
 
4.3%
7 13156
 
4.2%
5 13156
 
4.2%
4 11946
 
3.8%
8 11946
 
3.8%
Other values (40) 143198
46.1%

created_at
Categorical

HIGH CORRELATION  UNIFORM 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
2024-03-05 07:35:04
 
22
2024-03-05 12:53:59
 
22
2024-03-06 01:37:50
 
22
2024-03-06 02:09:40
 
22
2024-03-06 05:26:45
 
22
Other values (14)
308 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters7942
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-05 07:35:04
2nd row2024-03-05 07:35:04
3rd row2024-03-05 07:35:04
4th row2024-03-05 07:35:04
5th row2024-03-05 07:35:04

Common Values

ValueCountFrequency (%)
2024-03-05 07:35:04 22
 
5.3%
2024-03-05 12:53:59 22
 
5.3%
2024-03-06 01:37:50 22
 
5.3%
2024-03-06 02:09:40 22
 
5.3%
2024-03-06 05:26:45 22
 
5.3%
2024-03-06 05:40:04 22
 
5.3%
2024-03-06 05:45:20 22
 
5.3%
2024-03-06 11:39:06 22
 
5.3%
2024-03-12 11:01:20 22
 
5.3%
2024-03-23 02:13:16 22
 
5.3%
Other values (9) 198
47.4%

Length

2024-04-19T06:50:49.833796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-03-06 132
 
15.8%
2024-04-12 132
 
15.8%
2024-03-05 44
 
5.3%
2024-03-23 44
 
5.3%
02:15:29 22
 
2.6%
11:06:06 22
 
2.6%
08:37:55 22
 
2.6%
06:42:25 22
 
2.6%
02:56:29 22
 
2.6%
01:29:11 22
 
2.6%
Other values (16) 352
42.1%

Most occurring characters

ValueCountFrequency (%)
0 1650
20.8%
2 1386
17.5%
4 836
10.5%
- 836
10.5%
: 836
10.5%
1 528
 
6.6%
3 506
 
6.4%
418
 
5.3%
5 374
 
4.7%
6 286
 
3.6%
Other values (3) 286
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1650
20.8%
2 1386
17.5%
4 836
10.5%
- 836
10.5%
: 836
10.5%
1 528
 
6.6%
3 506
 
6.4%
418
 
5.3%
5 374
 
4.7%
6 286
 
3.6%
Other values (3) 286
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1650
20.8%
2 1386
17.5%
4 836
10.5%
- 836
10.5%
: 836
10.5%
1 528
 
6.6%
3 506
 
6.4%
418
 
5.3%
5 374
 
4.7%
6 286
 
3.6%
Other values (3) 286
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1650
20.8%
2 1386
17.5%
4 836
10.5%
- 836
10.5%
: 836
10.5%
1 528
 
6.6%
3 506
 
6.4%
418
 
5.3%
5 374
 
4.7%
6 286
 
3.6%
Other values (3) 286
 
3.6%

updated_at
Categorical

HIGH CORRELATION  UNIFORM 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size31.2 KiB
2024-03-06 03:23:01
 
22
2024-03-06 01:49:10
 
22
2024-03-06 05:14:43
 
22
2024-03-06 05:24:27
 
22
2024-03-06 13:03:37
 
22
Other values (14)
308 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters7942
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-06 03:23:01
2nd row2024-03-06 03:23:01
3rd row2024-03-06 03:23:01
4th row2024-03-06 03:23:01
5th row2024-03-06 03:23:01

Common Values

ValueCountFrequency (%)
2024-03-06 03:23:01 22
 
5.3%
2024-03-06 01:49:10 22
 
5.3%
2024-03-06 05:14:43 22
 
5.3%
2024-03-06 05:24:27 22
 
5.3%
2024-03-06 13:03:37 22
 
5.3%
2024-03-06 05:43:56 22
 
5.3%
2024-03-06 05:54:55 22
 
5.3%
2024-03-06 12:49:41 22
 
5.3%
2024-03-12 11:27:33 22
 
5.3%
2024-04-12 07:29:56 22
 
5.3%
Other values (9) 198
47.4%

Length

2024-04-19T06:50:49.885771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-04-12 198
23.7%
2024-03-06 176
21.1%
01:49:10 22
 
2.6%
06:45:22 22
 
2.6%
12:08:44 22
 
2.6%
11:04:36 22
 
2.6%
06:43:10 22
 
2.6%
06:13:15 22
 
2.6%
02:26:48 22
 
2.6%
02:04:56 22
 
2.6%
Other values (13) 286
34.2%

Most occurring characters

ValueCountFrequency (%)
0 1518
19.1%
2 1342
16.9%
4 990
12.5%
- 836
10.5%
: 836
10.5%
1 594
 
7.5%
3 484
 
6.1%
418
 
5.3%
6 352
 
4.4%
5 330
 
4.2%
Other values (3) 242
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1518
19.1%
2 1342
16.9%
4 990
12.5%
- 836
10.5%
: 836
10.5%
1 594
 
7.5%
3 484
 
6.1%
418
 
5.3%
6 352
 
4.4%
5 330
 
4.2%
Other values (3) 242
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1518
19.1%
2 1342
16.9%
4 990
12.5%
- 836
10.5%
: 836
10.5%
1 594
 
7.5%
3 484
 
6.1%
418
 
5.3%
6 352
 
4.4%
5 330
 
4.2%
Other values (3) 242
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7942
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1518
19.1%
2 1342
16.9%
4 990
12.5%
- 836
10.5%
: 836
10.5%
1 594
 
7.5%
3 484
 
6.1%
418
 
5.3%
6 352
 
4.4%
5 330
 
4.2%
Other values (3) 242
 
3.0%

rule
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size38.2 KiB
{"step": "same", "level": 2}
264 
{"step": "same", "level": 2, "has_streak": true}
88 
{"step": "same", "level": 2, "has_perseverance": true}
66 

Length

Max length54
Median length28
Mean length36.315789
Min length28

Characters and Unicode

Total characters15180
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row{"step": "same", "level": 2, "has_streak": true}
2nd row{"step": "same", "level": 2, "has_streak": true}
3rd row{"step": "same", "level": 2, "has_streak": true}
4th row{"step": "same", "level": 2, "has_streak": true}
5th row{"step": "same", "level": 2, "has_streak": true}

Common Values

ValueCountFrequency (%)
{"step": "same", "level": 2} 264
63.2%
{"step": "same", "level": 2, "has_streak": true} 88
 
21.1%
{"step": "same", "level": 2, "has_perseverance": true} 66
 
15.8%

Length

2024-04-19T06:50:49.939296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:49.993331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
step 418
21.1%
same 418
21.1%
level 418
21.1%
2 418
21.1%
true 154
 
7.8%
has_streak 88
 
4.4%
has_perseverance 66
 
3.3%

Most occurring characters

ValueCountFrequency (%)
" 2816
18.6%
e 2178
14.3%
1562
10.3%
s 1144
 
7.5%
: 990
 
6.5%
l 836
 
5.5%
a 726
 
4.8%
t 660
 
4.3%
, 572
 
3.8%
p 484
 
3.2%
Other values (12) 3212
21.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15180
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 2816
18.6%
e 2178
14.3%
1562
10.3%
s 1144
 
7.5%
: 990
 
6.5%
l 836
 
5.5%
a 726
 
4.8%
t 660
 
4.3%
, 572
 
3.8%
p 484
 
3.2%
Other values (12) 3212
21.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15180
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 2816
18.6%
e 2178
14.3%
1562
10.3%
s 1144
 
7.5%
: 990
 
6.5%
l 836
 
5.5%
a 726
 
4.8%
t 660
 
4.3%
, 572
 
3.8%
p 484
 
3.2%
Other values (12) 3212
21.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15180
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 2816
18.6%
e 2178
14.3%
1562
10.3%
s 1144
 
7.5%
: 990
 
6.5%
l 836
 
5.5%
a 726
 
4.8%
t 660
 
4.3%
, 572
 
3.8%
p 484
 
3.2%
Other values (12) 3212
21.2%

cefr_rate
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.403158
Minimum0
Maximum50
Zeros66
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:50.046652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116.67
median21.43
Q325
95-th percentile50
Maximum50
Range50
Interquartile range (IQR)8.33

Descriptive statistics

Standard deviation11.135851
Coefficient of variation (CV)0.57391951
Kurtosis1.5384088
Mean19.403158
Median Absolute Deviation (MAD)3.57
Skewness0.28666107
Sum8110.52
Variance124.00717
MonotonicityNot monotonic
2024-04-19T06:50:50.099100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
25 132
31.6%
16.67 66
15.8%
0 66
15.8%
21.43 22
 
5.3%
22.22 22
 
5.3%
12.5 22
 
5.3%
50 22
 
5.3%
20.83 22
 
5.3%
18.75 22
 
5.3%
22.92 22
 
5.3%
ValueCountFrequency (%)
0 66
15.8%
12.5 22
 
5.3%
16.67 66
15.8%
18.75 22
 
5.3%
20.83 22
 
5.3%
21.43 22
 
5.3%
22.22 22
 
5.3%
22.92 22
 
5.3%
25 132
31.6%
50 22
 
5.3%
ValueCountFrequency (%)
50 22
 
5.3%
25 132
31.6%
22.92 22
 
5.3%
22.22 22
 
5.3%
21.43 22
 
5.3%
20.83 22
 
5.3%
18.75 22
 
5.3%
16.67 66
15.8%
12.5 22
 
5.3%
0 66
15.8%

points
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.210526
Minimum0
Maximum72
Zeros44
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:50.150212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median35
Q356
95-th percentile72
Maximum72
Range72
Interquartile range (IQR)51

Descriptive statistics

Standard deviation24.514738
Coefficient of variation (CV)0.76107845
Kurtosis-1.581948
Mean32.210526
Median Absolute Deviation (MAD)23
Skewness0.002408675
Sum13464
Variance600.97236
MonotonicityNot monotonic
2024-04-19T06:50:50.207171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
58 44
 
10.5%
5 44
 
10.5%
0 44
 
10.5%
56 44
 
10.5%
41 22
 
5.3%
55 22
 
5.3%
45 22
 
5.3%
8 22
 
5.3%
10 22
 
5.3%
2 22
 
5.3%
Other values (5) 110
26.3%
ValueCountFrequency (%)
0 44
10.5%
2 22
5.3%
5 44
10.5%
8 22
5.3%
10 22
5.3%
20 22
5.3%
25 22
5.3%
35 22
5.3%
41 22
5.3%
45 22
5.3%
ValueCountFrequency (%)
72 22
5.3%
61 22
5.3%
58 44
10.5%
56 44
10.5%
55 22
5.3%
45 22
5.3%
41 22
5.3%
35 22
5.3%
25 22
5.3%
20 22
5.3%

score
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
0.0
374 
13.71
 
22
12.56
 
22

Length

Max length5
Median length3
Mean length3.2105263
Min length3

Characters and Unicode

Total characters1342
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 374
89.5%
13.71 22
 
5.3%
12.56 22
 
5.3%

Length

2024-04-19T06:50:50.274487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:50.330217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 374
89.5%
13.71 22
 
5.3%
12.56 22
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 748
55.7%
. 418
31.1%
1 66
 
4.9%
3 22
 
1.6%
7 22
 
1.6%
2 22
 
1.6%
5 22
 
1.6%
6 22
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1342
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 748
55.7%
. 418
31.1%
1 66
 
4.9%
3 22
 
1.6%
7 22
 
1.6%
2 22
 
1.6%
5 22
 
1.6%
6 22
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1342
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 748
55.7%
. 418
31.1%
1 66
 
4.9%
3 22
 
1.6%
7 22
 
1.6%
2 22
 
1.6%
5 22
 
1.6%
6 22
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1342
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 748
55.7%
. 418
31.1%
1 66
 
4.9%
3 22
 
1.6%
7 22
 
1.6%
2 22
 
1.6%
5 22
 
1.6%
6 22
 
1.6%

time_spent
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448.84211
Minimum0
Maximum3063
Zeros22
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-19T06:50:50.377491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167
median186
Q3411
95-th percentile3063
Maximum3063
Range3063
Interquartile range (IQR)344

Descriptive statistics

Standard deviation731.09507
Coefficient of variation (CV)1.6288469
Kurtosis6.1312213
Mean448.84211
Median Absolute Deviation (MAD)144
Skewness2.5940651
Sum187616
Variance534500
MonotonicityNot monotonic
2024-04-19T06:50:50.431208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1121 22
 
5.3%
230 22
 
5.3%
3063 22
 
5.3%
1597 22
 
5.3%
42 22
 
5.3%
102 22
 
5.3%
67 22
 
5.3%
37 22
 
5.3%
0 22
 
5.3%
77 22
 
5.3%
Other values (9) 198
47.4%
ValueCountFrequency (%)
0 22
5.3%
30 22
5.3%
37 22
5.3%
42 22
5.3%
67 22
5.3%
77 22
5.3%
102 22
5.3%
121 22
5.3%
153 22
5.3%
186 22
5.3%
ValueCountFrequency (%)
3063 22
5.3%
1597 22
5.3%
1121 22
5.3%
458 22
5.3%
411 22
5.3%
332 22
5.3%
301 22
5.3%
230 22
5.3%
200 22
5.3%
186 22
5.3%

completed_at
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct8
Distinct (%)4.5%
Missing242
Missing (%)57.9%
Memory size20.8 KiB
2024-03-06 03:23:01
22 
2024-03-06 01:49:10
22 
2024-03-06 05:14:43
22 
2024-03-06 05:24:27
22 
2024-04-12 02:04:56
22 
Other values (3)
66 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters3344
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-06 03:23:01
2nd row2024-03-06 03:23:01
3rd row2024-03-06 03:23:01
4th row2024-03-06 03:23:01
5th row2024-03-06 03:23:01

Common Values

ValueCountFrequency (%)
2024-03-06 03:23:01 22
 
5.3%
2024-03-06 01:49:10 22
 
5.3%
2024-03-06 05:14:43 22
 
5.3%
2024-03-06 05:24:27 22
 
5.3%
2024-04-12 02:04:56 22
 
5.3%
2024-04-12 02:26:48 22
 
5.3%
2024-04-12 11:04:36 22
 
5.3%
2024-04-12 12:08:44 22
 
5.3%
(Missing) 242
57.9%

Length

2024-04-19T06:50:50.488260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:50.546842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-06 88
25.0%
2024-04-12 88
25.0%
03:23:01 22
 
6.2%
01:49:10 22
 
6.2%
05:14:43 22
 
6.2%
05:24:27 22
 
6.2%
02:04:56 22
 
6.2%
02:26:48 22
 
6.2%
11:04:36 22
 
6.2%
12:08:44 22
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 682
20.4%
2 594
17.8%
4 462
13.8%
- 352
10.5%
: 352
10.5%
1 242
 
7.2%
3 176
 
5.3%
176
 
5.3%
6 154
 
4.6%
5 66
 
2.0%
Other values (3) 88
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 682
20.4%
2 594
17.8%
4 462
13.8%
- 352
10.5%
: 352
10.5%
1 242
 
7.2%
3 176
 
5.3%
176
 
5.3%
6 154
 
4.6%
5 66
 
2.0%
Other values (3) 88
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 682
20.4%
2 594
17.8%
4 462
13.8%
- 352
10.5%
: 352
10.5%
1 242
 
7.2%
3 176
 
5.3%
176
 
5.3%
6 154
 
4.6%
5 66
 
2.0%
Other values (3) 88
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 682
20.4%
2 594
17.8%
4 462
13.8%
- 352
10.5%
: 352
10.5%
1 242
 
7.2%
3 176
 
5.3%
176
 
5.3%
6 154
 
4.6%
5 66
 
2.0%
Other values (3) 88
 
2.6%

total_time
Categorical

HIGH CORRELATION  MISSING  UNIFORM 

Distinct18
Distinct (%)4.5%
Missing22
Missing (%)5.3%
Memory size26.0 KiB
00:17:16
 
22
00:06:51
 
22
00:05:32
 
22
00:07:38
 
22
00:05:01
 
22
Other values (13)
286 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3168
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:17:16
2nd row00:17:16
3rd row00:17:16
4th row00:17:16
5th row00:17:16

Common Values

ValueCountFrequency (%)
00:17:16 22
 
5.3%
00:06:51 22
 
5.3%
00:05:32 22
 
5.3%
00:07:38 22
 
5.3%
00:05:01 22
 
5.3%
00:03:06 22
 
5.3%
00:02:33 22
 
5.3%
00:03:20 22
 
5.3%
00:02:01 22
 
5.3%
00:01:17 22
 
5.3%
Other values (8) 176
42.1%

Length

2024-04-19T06:50:50.616223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:17:16 22
 
5.6%
00:06:51 22
 
5.6%
00:51:03 22
 
5.6%
00:07:45 22
 
5.6%
00:00:42 22
 
5.6%
00:01:42 22
 
5.6%
00:01:07 22
 
5.6%
00:00:37 22
 
5.6%
00:03:50 22
 
5.6%
00:01:17 22
 
5.6%
Other values (8) 176
44.4%

Most occurring characters

ValueCountFrequency (%)
0 1386
43.8%
: 792
25.0%
1 220
 
6.9%
3 220
 
6.9%
7 132
 
4.2%
5 132
 
4.2%
2 132
 
4.2%
6 66
 
2.1%
4 66
 
2.1%
8 22
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3168
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1386
43.8%
: 792
25.0%
1 220
 
6.9%
3 220
 
6.9%
7 132
 
4.2%
5 132
 
4.2%
2 132
 
4.2%
6 66
 
2.1%
4 66
 
2.1%
8 22
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3168
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1386
43.8%
: 792
25.0%
1 220
 
6.9%
3 220
 
6.9%
7 132
 
4.2%
5 132
 
4.2%
2 132
 
4.2%
6 66
 
2.1%
4 66
 
2.1%
8 22
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3168
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1386
43.8%
: 792
25.0%
1 220
 
6.9%
3 220
 
6.9%
7 132
 
4.2%
5 132
 
4.2%
2 132
 
4.2%
6 66
 
2.1%
4 66
 
2.1%
8 22
 
0.7%

queues
Categorical

HIGH CORRELATION  UNIFORM 

Distinct19
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
 
22
[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685]
 
22
[45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713]
 
22
[47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883]
 
22
[18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248]
 
22
Other values (14)
308 

Length

Max length84
Median length70
Mean length68.157895
Min length28

Characters and Unicode

Total characters28490
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
2nd row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
3rd row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
4th row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]
5th row[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]

Common Values

ValueCountFrequency (%)
[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823] 22
 
5.3%
[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685] 22
 
5.3%
[45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713] 22
 
5.3%
[47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883] 22
 
5.3%
[18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248] 22
 
5.3%
[18227, 18230, 18235, 18225] 22
 
5.3%
[18215, 18217, 18223, 18213, 18214, 18216, 18218, 18219, 18220] 22
 
5.3%
[46120, 46127, 46157, 46163, 46169, 46174, 46185, 46187, 46194, 46197] 22
 
5.3%
[46208, 46209, 46210, 46211, 46212, 46213, 46214, 46215, 46216, 46217] 22
 
5.3%
[54546, 54547, 54548, 54549, 54550, 54551, 54847, 54553, 54554, 54555] 22
 
5.3%
Other values (9) 198
47.4%

Length

2024-04-19T06:50:50.671605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
45764 22
 
0.5%
54596 22
 
0.5%
54582 22
 
0.5%
54583 22
 
0.5%
54584 22
 
0.5%
54585 22
 
0.5%
54587 22
 
0.5%
54588 22
 
0.5%
54589 22
 
0.5%
54592 22
 
0.5%
Other values (175) 3850
94.6%

Most occurring characters

ValueCountFrequency (%)
4 4026
14.1%
5 3916
13.7%
, 3652
12.8%
3652
12.8%
8 2486
8.7%
7 2222
7.8%
1 1980
6.9%
6 1848
6.5%
2 1606
 
5.6%
0 968
 
3.4%
Other values (4) 2134
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28490
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4 4026
14.1%
5 3916
13.7%
, 3652
12.8%
3652
12.8%
8 2486
8.7%
7 2222
7.8%
1 1980
6.9%
6 1848
6.5%
2 1606
 
5.6%
0 968
 
3.4%
Other values (4) 2134
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28490
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4 4026
14.1%
5 3916
13.7%
, 3652
12.8%
3652
12.8%
8 2486
8.7%
7 2222
7.8%
1 1980
6.9%
6 1848
6.5%
2 1606
 
5.6%
0 968
 
3.4%
Other values (4) 2134
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28490
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4 4026
14.1%
5 3916
13.7%
, 3652
12.8%
3652
12.8%
8 2486
8.7%
7 2222
7.8%
1 1980
6.9%
6 1848
6.5%
2 1606
 
5.6%
0 968
 
3.4%
Other values (4) 2134
7.5%

class_test_id
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing418
Missing (%)100.0%
Memory size3.4 KiB

attempted_sets
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing418
Missing (%)100.0%
Memory size3.4 KiB

type
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size26.7 KiB
homework
418 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3344
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhomework
2nd rowhomework
3rd rowhomework
4th rowhomework
5th rowhomework

Common Values

ValueCountFrequency (%)
homework 418
100.0%

Length

2024-04-19T06:50:50.727179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:50.772741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
homework 418
100.0%

Most occurring characters

ValueCountFrequency (%)
o 836
25.0%
h 418
12.5%
m 418
12.5%
e 418
12.5%
w 418
12.5%
r 418
12.5%
k 418
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 836
25.0%
h 418
12.5%
m 418
12.5%
e 418
12.5%
w 418
12.5%
r 418
12.5%
k 418
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 836
25.0%
h 418
12.5%
m 418
12.5%
e 418
12.5%
w 418
12.5%
r 418
12.5%
k 418
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3344
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 836
25.0%
h 418
12.5%
m 418
12.5%
e 418
12.5%
w 418
12.5%
r 418
12.5%
k 418
12.5%

has_glang_contrib
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
1
418 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters418
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 418
100.0%

Length

2024-04-19T06:50:50.821353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T06:50:50.866459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 418
100.0%

Most occurring characters

ValueCountFrequency (%)
1 418
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 418
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 418
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 418
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 418
100.0%

Interactions

2024-04-19T06:50:47.898071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:45.883682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.213177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.514426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.823144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.274959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.583331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.948031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:45.940115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.257285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.557984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.866091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.318941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.629425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.993136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:45.985891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.301580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.600827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.070125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.363476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.672760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:48.039588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.029782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.342569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.641624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.111401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.405342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.714318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:48.081842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.073407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.383363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.684587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.149903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.446883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.756762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:48.127409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.117670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.425605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.728294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.189422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.491398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.800503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:48.173574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.166971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.471103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:46.776961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.232125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.539746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T06:50:47.849900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T06:50:50.909994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cefr_ratecompleted_atcreated_atengineevent_idfailgroup_idhistoryiditemslesson_idloadpasspointsqueuesroundrulescorestatustime_spenttotal_timeupdated_at
cefr_rate1.0000.9830.9830.507-0.2160.9860.5000.984-0.1350.983-0.214-0.5020.9830.3330.9830.2990.4640.3430.5640.1760.9830.983
completed_at0.9831.0001.0000.9830.9521.0000.9831.0000.9761.0000.9520.1091.0000.3861.0000.9880.9830.9851.0000.3101.0001.000
created_at0.9831.0001.0000.9790.9041.0000.9810.9991.0001.0000.8630.2441.000-0.0511.0000.9820.9810.9810.981-0.4051.0001.000
engine0.5070.9830.9791.0000.4280.9800.5050.9810.2340.9790.3890.5700.980-0.1660.9790.9980.2040.2850.6370.0190.9790.979
event_id-0.2160.9520.9040.4281.0000.9800.9990.9810.9040.9790.9840.4470.9800.1340.9790.3220.2840.3180.000-0.2190.9790.979
fail0.9861.0001.0000.9800.9801.0000.9821.0000.8021.0000.9780.3791.0000.1541.0000.9840.9820.9820.9820.0551.0001.000
group_id0.5000.9830.9810.5050.9990.9821.0000.9820.8020.9810.9060.4980.9810.0630.9810.4880.2520.2200.406-0.3740.9810.981
history0.9841.0000.9990.9810.9811.0000.9821.0000.3950.9990.101-0.1061.000-0.7930.9990.9830.9820.9820.982-0.5451.0000.999
id-0.1350.9761.0000.2340.9040.8020.8020.3951.0000.9830.8630.2440.984-0.0510.9830.3590.6070.3440.336-0.4050.9830.983
items0.9831.0001.0000.9790.9791.0000.9810.9990.9831.0000.9700.3881.0000.1841.0000.9820.9810.9810.981-0.1261.0001.000
lesson_id-0.2140.9520.8630.3890.9840.9780.9060.1010.8630.9701.0000.4250.9840.1930.9830.5020.3680.2090.500-0.1750.9830.983
load-0.5020.1090.2440.5700.4470.3790.498-0.1060.2440.3880.4251.0000.9900.2760.9880.8490.5680.2860.7980.0790.9880.988
pass0.9831.0001.0000.9800.9801.0000.9811.0000.9841.0000.9840.9901.0000.3761.0000.9830.9810.9810.9810.0121.0001.000
points0.3330.386-0.051-0.1660.1340.1540.063-0.793-0.0510.1840.1930.2760.3761.0000.9890.7130.6980.5230.9080.5100.9900.989
queues0.9831.0001.0000.9790.9791.0000.9810.9990.9831.0000.9830.9881.0000.9891.0000.9820.9810.9810.981-0.1261.0001.000
round0.2990.9880.9820.9980.3220.9840.4880.9830.3590.9820.5020.8490.9830.7130.9821.0000.2650.1890.5280.1020.9820.982
rule0.4640.9830.9810.2040.2840.9820.2520.9820.6070.9810.3680.5680.9810.6980.9810.2651.0000.4660.457-0.2540.9810.981
score0.3430.9850.9810.2850.3180.9820.2200.9820.3440.9810.2090.2860.9810.5230.9810.1890.4661.0000.2770.5300.9810.981
status0.5641.0000.9810.6370.0000.9820.4060.9820.3360.9810.5000.7980.9810.9080.9810.5280.4570.2771.0000.4120.9810.981
time_spent0.1760.310-0.4050.019-0.2190.055-0.374-0.545-0.405-0.126-0.1750.0790.0120.510-0.1260.102-0.2540.5300.4121.0000.9830.983
total_time0.9831.0001.0000.9790.9791.0000.9811.0000.9831.0000.9830.9881.0000.9901.0000.9820.9810.9810.9810.9831.0001.000
updated_at0.9831.0001.0000.9790.9791.0000.9810.9990.9831.0000.9830.9881.0000.9891.0000.9820.9810.9810.9810.9831.0001.000

Missing values

2024-04-19T06:50:48.259461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T06:50:48.415531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-04-19T06:50:48.504572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

iduser_idlesson_idgroup_idevent_idengineitemsloadpassfailroundstatushistorycreated_atupdated_atrulecefr_ratepointsscoretime_spentcompleted_attotal_timequeuesclass_test_idattempted_setstypehas_glang_contrib
02369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
12369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
22369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
32369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
42369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
52369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
62369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
72369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
82369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
92369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]NaNNaNhomework1
iduser_idlesson_idgroup_idevent_idengineitemsloadpassfailroundstatushistorycreated_atupdated_atrulecefr_ratepointsscoretime_spentcompleted_attotal_timequeuesclass_test_idattempted_setstypehas_glang_contrib
40825073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
40925073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41025073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41125073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41225073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41325073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41425073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41525073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41625073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1
41725073253421191760279718carryForwardEngine[54781, 54783, 54784, 54787, 54788, 54789, 54790, 54782, 54785, 54786]7[54781, 54783, 54784, 54787, 54788, 54789, 54790]NaN2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [54782, 54785, 54786], "passed": [54781, 54783, 54784, 54787, 54788, 54789, 54790], "points": 35, "attempted": [54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790], "cefr_rate": 16.666666666666668, "created_at": "2024-04-12T12:15:58.415290Z", "lang_level": 1, "time_spent": "30"}}, "cefr_rate": {"1712923853": 25, "1712923854": 12.5, "1712923855": 18.75, "1712923856": 18.75, "1712923857": 14.583333335, "1712923858": 12.5, "1712923859": 16.666666666666668, "1712923860": 16.666666666666668, "1712923861": 16.666666666666668}, "first_engine": "linearStandAloneEngine", "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-04-12 12:10:372024-04-12 12:15:58{"step": "same", "level": 2}16.6735.00.030.0NaN00:00:30[54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790]NaNNaNhomework1

Duplicate rows

Most frequently occurring

iduser_idlesson_idgroup_idevent_idengineitemsloadpassfailroundstatushistorycreated_atupdated_atrulecefr_ratepointsscoretime_spentcompleted_attotal_timequeuestypehas_glang_contrib# duplicates
02369225341855171720789linearStandAloneEngine[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]9[45767, 45766, 45818, 45819, 45820, 45821, 45822, 45823][45764, 45765]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [45764, 45765], "passed": [45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "points": 58, "attempted": [45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823], "cefr_rate": 21.42857143, "created_at": "2024-03-06T03:23:01.358506Z", "lang_level": 1, "time_spent": "1121"}}, "cefr_rate": {"1709690758": 6.25, "1709690759": 15.00000001, "1709690760": 16.66666667, "1709690761": 17.85714286, "1709690762": 21.42857143, "1709690763": 21.42857143}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T03:23:01.358549Z", "streak_badge_given_at_index": 6}2024-03-05 07:35:042024-03-06 03:23:01{"step": "same", "level": 2, "has_streak": true}21.4358.00.01121.02024-03-06 03:23:0100:17:16[45764, 45765, 45766, 45767, 45818, 45819, 45820, 45821, 45822, 45823]homework122
12372725341187171720787linearStandAloneEngine[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685]9[26680, 26681, 26686, 26683, 26684, 26685][26687, 26688, 26689, 26682]1passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "linearStandAloneEngine", "failed": [26687, 26688, 26689, 26682], "passed": [26680, 26681, 26686, 26683, 26684, 26685], "points": 41, "attempted": [26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685], "cefr_rate": 16.666666666666668, "created_at": "2024-03-06T01:49:10.324478Z", "lang_level": 1, "time_spent": "385"}}, "cefr_rate": {"1709688394": 25, "1709688395": 25, "1709688396": 25, "1709688397": 18.75, "1709688398": 16.666666665, "1709688399": 15.625, "1709688400": 15.625, "1709688401": 14.583333333333334, "1709688402": 15.972222223333333}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1187, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T01:49:10.324516Z", "perseverance_badge_given_at_index": 6}2024-03-05 12:53:592024-03-06 01:49:10{"step": "same", "level": 2}16.6741.00.0411.02024-03-06 01:49:1000:06:51[26680, 26681, 26686, 26687, 26688, 26689, 26682, 26683, 26684, 26685]homework122
22373325341556171720788carryForwardEngine[45704, 45705, 45706, 45707]3[45708, 45709, 45710, 45711, 45712, 45713, 45706, 45707][45704, 45705]3passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [45708, 45709, 45710, 45711, 45712, 45713], "points": 35, "attempted": [45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713], "cefr_rate": 18.75, "created_at": "2024-03-06T04:21:19.940552Z", "lang_level": 1, "time_spent": "250"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705, 45706, 45707], "passed": [], "points": 36, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 18.75, "created_at": "2024-03-06T04:24:16.034067Z", "lang_level": 1, "time_spent": "300"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [45704, 45705], "passed": [45706, 45707], "points": 58, "attempted": [45704, 45705, 45706, 45707], "cefr_rate": 25, "created_at": "2024-03-06T05:14:42.956894Z", "lang_level": 1, "time_spent": "328"}}, "cefr_rate": {"1709689884": 8.33333333, "1709689885": 12.5, "1709689886": 18.75, "1709689887": 18.75, "1709689888": 18.75, "1709689889": 18.75, "1709689890": 18.75, "1709689891": 18.75, "1709689892": 18.75, "1709689893": 18.75, "1709689894": 21.875}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1556, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:14:42.956942Z", "streak_badge_given_at_index": 8, "perseverance_badge_given_at_index": 3}2024-03-06 01:37:502024-03-06 05:14:43{"step": "same", "level": 2}25.0058.00.0332.02024-03-06 05:14:4300:05:32[45704, 45705, 45706, 45707, 45708, 45709, 45710, 45711, 45712, 45713]homework122
32373525341856171720790carryForwardEngine[47871, 47877, 47880]2[47692, 47857, 47860, 47863, 47866, 47883, 47874, 47871][47877, 47880]4passed{"badge": {"first_lesson_achiever": true}, "bonus": {"": 100}, "round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [47692, 47857, 47860, 47863, 47866, 47883], "points": 33, "attempted": [47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:12:51.624980Z", "lang_level": 1, "time_spent": "379"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47874, 47877, 47880], "passed": [], "points": 34, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 13.095238095, "created_at": "2024-03-06T04:14:17.787087Z", "lang_level": 1, "time_spent": "386"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [47871, 47877, 47880], "passed": [47874], "points": 40, "attempted": [47871, 47874, 47877, 47880], "cefr_rate": 14.880952385, "created_at": "2024-03-06T05:23:03.040310Z", "lang_level": 1, "time_spent": "453"}, "4": {"score": 0, "engine": "carryForwardEngine", "failed": [47877, 47880], "passed": [47871], "points": 55, "attempted": [47871, 47877, 47880], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:24:27.318589Z", "lang_level": 1, "time_spent": "456"}}, "cefr_rate": {"1709691177": 25, "1709691178": 25, "1709691179": 25, "1709691180": 25, "1709691181": 25, "1709691182": 20.83333333, "1709691183": 17.85714286, "1709691184": 17.85714286, "1709691185": 17.85714286, "1709691186": 13.095238095, "1709691187": 13.095238095, "1709691188": 13.095238095, "1709691189": 13.095238095, "1709691190": 14.880952385, "1709691191": 14.880952385, "1709691192": 16.666666665, "1709691193": 16.666666665}, "skills_count": 0, "weakest_skill": "", "next_lesson_id": 1856, "is_weakest_skill_on": true, "lesson_completed_at": "2024-03-06T05:24:27.318622Z", "streak_badge_given_at_index": 4, "perseverance_badge_given_at_index": 3}2024-03-06 02:09:402024-03-06 05:24:27{"step": "same", "level": 2}16.6755.00.0458.02024-03-06 05:24:2700:07:38[47692, 47857, 47860, 47863, 47866, 47871, 47874, 47877, 47880, 47883]homework122
4237542534921170019951carryForwardEngine[18243, 18237, 18240, 18241, 18244, 18245]5[18246, 18239, 18242, 18248, 18238, 18247, 18243, 18240][18237, 18241, 18244]4assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18246], "passed": [], "points": 0, "attempted": [18238, 18243, 18246], "cefr_rate": 0, "created_at": "2024-03-06T05:31:34.736440Z", "lang_level": 1, "time_spent": "244"}, "2": {"score": 0, "engine": "carryForwardEngine", "failed": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "passed": [18246, 18239, 18242, 18248], "points": 22, "attempted": [18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248], "cefr_rate": 16.666666665, "created_at": "2024-03-06T05:37:32.250476Z", "lang_level": 1, "time_spent": "286"}, "3": {"score": 0, "engine": "carryForwardEngine", "failed": [18243, 18237, 18240, 18241, 18244, 18245], "passed": [18238, 18247], "points": 35, "attempted": [18238, 18243, 18237, 18240, 18241, 18244, 18245, 18247], "cefr_rate": 16.666666666666668, "created_at": "2024-03-06T13:01:24.927075Z", "lang_level": 1, "time_spent": "294"}}, "cefr_rate": {"1709703166": 25, "1709703167": 25, "1709703168": 25, "1709703169": 25, "1709703170": 25, "1709703171": 25, "1709703172": 25, "1709703173": 25, "1709703174": 25, "1709703175": 20.833333335, "1709703176": 20.833333335, "1709703177": 20.833333335, "1709703178": 20.833333335, "1709703179": 20.833333335, "1709703180": 20.833333335, "1709703181": 20.833333335, "1709703182": 19.444444446666665, "1709703183": 19.444444446666665, "1709703184": 22.222222223333333, "1709703185": 22.222222223333333, "1709703186": 22.222222223333333}, "skills_count": {"reading": 1, "writing": 1, "listening": 1}, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 4}2024-03-06 05:26:452024-03-06 13:03:37{"step": "same", "level": 2}22.2245.00.0301.0NaN00:05:01[18238, 18243, 18246, 18237, 18239, 18240, 18241, 18242, 18244, 18245, 18247, 18248]homework122
5237552534943170019952carryForwardEngine[18227, 18235, 18225]1[18230][18227]2assessment{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18227, 18235], "passed": [18230], "points": 5, "attempted": [18227, 18230, 18235], "cefr_rate": 25, "created_at": "2024-03-06T05:43:24.441419Z", "lang_level": 1, "time_spent": "185"}}, "cefr_rate": {"1709703758": 25, "1709703759": 25}, "skills_count": {"reading": 1, "listening": 2}, "weakest_skill": "listening", "is_weakest_skill_on": true}2024-03-06 05:40:042024-03-06 05:43:56{"step": "same", "level": 2}25.005.00.0186.0NaN00:03:06[18227, 18230, 18235, 18225]homework122
6237562534944170019953carryForwardEngine[18215, 18223, 18213, 18214, 18216, 18218, 18219, 18220]0[18217]NaN2in_progress{"round": {"1": {"score": 0, "engine": "carryForwardEngine", "failed": [18215, 18223], "passed": [18217], "points": 5, "attempted": [18215, 18217, 18223], "cefr_rate": 25, "created_at": "2024-03-06T05:54:55.204051Z", "lang_level": 1, "time_spent": "153"}}, "cefr_rate": {"1709704027": 25}, "skills_count": {"writing": 1, "listening": 2}, "weakest_skill": "listening", "is_weakest_skill_on": true}2024-03-06 05:45:202024-03-06 05:54:55{"step": "same", "level": 2}25.005.00.0153.0NaN00:02:33[18215, 18217, 18223, 18213, 18214, 18216, 18218, 18219, 18220]homework122
72375925341615171721428linearStandAloneEngine[46120, 46127, 46157, 46163, 46169, 46174, 46185, 46187, 46194, 46197]9[46157][46120, 46127, 46163, 46169, 46174, 46185, 46187, 46194]1in_progress{"cefr_rate": {"1709725577": 50, "1709725578": 25, "1709725579": 16.66666667, "1709725580": 12.5, "1709725581": 12.5, "1709725582": 12.5, "1709725583": 12.5}, "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 6}2024-03-06 11:39:062024-03-06 12:49:41{"step": "same", "level": 2, "has_perseverance": true}12.508.00.0200.0NaN00:03:20[46120, 46127, 46157, 46163, 46169, 46174, 46185, 46187, 46194, 46197]homework122
82389225341616171721427linearStandAloneEngine[46208, 46209, 46210, 46211, 46212, 46213, 46214, 46215, 46216, 46217]2[46208, 46209][46210]1in_progress{"cefr_rate": {"1710242548": 50, "1710242549": 50}, "skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true}2024-03-12 11:01:202024-03-12 11:27:33{"step": "same", "level": 2}50.0010.00.0121.0NaN00:02:01[46208, 46209, 46210, 46211, 46212, 46213, 46214, 46215, 46216, 46217]homework122
924084253421121760279712linearStandAloneEngine[54546, 54547, 54548, 54549, 54550, 54551, 54847, 54553, 54554, 54555]8NaN[54546, 54550, 54551, 54847, 54553]1in_progress{"skills_count": 0, "weakest_skill": "", "is_weakest_skill_on": true, "perseverance_badge_given_at_index": 6}2024-03-23 02:13:162024-04-12 07:29:56{"step": "same", "level": 2, "has_perseverance": true}0.002.00.077.0NaN00:01:17[54546, 54547, 54548, 54549, 54550, 54551, 54847, 54553, 54554, 54555]homework122